Although I have mentioned the beta release of the repository earlier and noted as well that the student, Zubeida Khan, has won the CSIR prize of best Masters, that was 1-2 years ago and more has happened in the meantime.

From the technological viewpoint, there are more features available now than in the beta and MEDI’13 releases, such as the automated foundational interchangeability [2], and there’s more detail on the technologies used as well as an extended EER diagram for ontology storage and annotation, and it has an updated comparison with other repositories and usage statistics. Overall, it is the first attempt to realise the vision of an ontology library that was posed some 12 years ago in WonderWeb Deliverable D18, and it thus ended up having more features than those D18 requirements for a foundational ontology library. Have a look at ROMULUS online.

From a theoretical viewpoint, besides now having a book chapter on the mappings between the foundational ontologies [3], the ‘storyline’ and need for it—known very well in ontology engineering already—has been framed into one where the repository of the foundational ontologies is also needed for ontology-driven conceptual data modelling. Why is that so? There is an increasing amount of results on ontology-driven conceptual modelling (see ER’15 proceedings), which avails of foundational ontologies, such as UFO. There are multiple extensions to the conceptual modelling languages based on insights from ontology, and when they are based on different foundational ontologies, one can’t pick-and-choose anymore as there may be incompatibilities in how things are represented. Likewise, choosing for one foundational ontology limits, or enables, one to model one thing but not another. For instance, some do have ‘substance’ or ‘amount of matter’ (wine, alcohol and the like), others do not, so that there is, in theory, no place for such things in one’s conceptual data model. That’s not good—or at least complicates matters—for an information system or database that needs to store data about, say, a food processing plant or animal fodder. The paper presents more of such issues and how ROMULUS helps addressing them. Also, just like that ROMULUS can help choosing the most appropriate foundational ontology for ontology engineering and help analysing the foundational ontologies without reading umpteen papers on it first, it can do so for the conceptual modeller. Be this though ONSET or the web-based querying of the ontologies and their alignments.

Finally, in case you think there are shortcomings to the repository to the extent you feel the need to develop your own one: the paper provides ample material on how to build one yourself. If you don’t want to go through that trouble, then contact Zubeida or me for the feature request, and we’ll try to squeeze it in with the other activities.